similar to: Repeated measures cummulative logit mixed model

Hi all: How can I calculate the cumulative variance (or variance for each component) in correspondence analysis? If were possible in ADE4 package Thank you -- Antonio Punzón Merino O__---- Instituto Español de Oceanografía c/ /'_ --- Centro Oceanográfico de Santander (*) \(*) -- Promontorio de San Martín S/N ~~~~~~~~~~ 39004-Santander; Spain PO BOX: 240 Tlf: +34 942 29 10 60 Fax: +34

I have the following list of observations of calendar time: [1] 03-Nov-1997 09-Oct-1991 27-Aug-1992 01-Jul-1994 19-Jan-1990 12-Nov-1993 [7] 08-Oct-1993 10-Nov-1982 08-Dec-1986 23-Dec-1987 02-Aug-1995 20-Oct-1998 [13] 29-Apr-1991 16-Mar-1994 20-May-1991 28-Dec-1987 14-Jul-1999 27-Nov-1998 [19] 09-Sep-1999 26-Aug-1999 20-Jun-1997 05-May-1995 26-Mar-1998 15-Aug-1994 [25] 24-Jun-1996 02-Oct-1996

I have a form that I want to use to update multiple objects. In the controller, @grades = Grade.find(params[:grade].keys) @grades.each_with_index do |grade, i| grade.update_attribute(params[:grade][i]) end all_valid = @grades.inject(true) {|memo, c| c.valid? && memo } this doesn''t update the attributes as I would expect. (I would just use

I have grades data. I read them from a csv in letter-grade format. I then converted them to levels levels(grades$grade)=c('A+','A','A-','B+','B','B-','C+','C','C-','D+','D','D-') And then to numbers grades$gp=grades$grade levels(grades$gp)=c(4.3,4.0,3.7, 3.3,3.0,2.7, 2.3,2.0,1.7, 1.3,1.0,0.7)

I would like to create 15 box plots from two sets of data. Set1 - containts PayGrade, Min_Salary, Max_Salary data for 15 pay grades Set2 - contains PayGrade, Actual_Min, Actual_Max, and Actual_Mean for the 15 pay grades I would like 15 box plots (one for each paygrade) whose whiskers were the Min_Salary and Max_Salary data and whose ''box'' was Actual_Min, Actual_Mean,

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

Hi-- I am trying to normalize course grades for each instance of a course, e.g. Stats 1 Fall2009 J. Smith. I have a frame for all instances of a course, e.g. stats 1 in the last 5 years, that looks like SIDN TERM GRADE INST where SIDN is a Student ID Number, TERM is a factor that gives the quarter and year a course was offered, GRADE is a 0-4.3 grade and INST is the instructor, again as a

Env: R 2.8.1, Win Xp, Eclipse/StatET In a .Rd file, I have an example containing the lines: # calculate Y M, using polynomial contrasts trends <- as.matrix(VocabGrowth) %*% poly(8:11, degree=3) colnames(trends)<- c("Linear", "Quad", "Cubic") [At the risk of a long message, I'll append the complete .Rd file at the end of this message, in case this was

Dear List: I'm creating a series of barplots using Sweave that must assume a standard format. This is student achievement data and the x-axis must include all grades 3 to 8. In some cases, the data for a grade (or more than one grade) are missing in the vector math.bar, but are never missing for the vector apmxpmeet. The following sample code illustrates the issue. Using the code below to

In a previous post, I mentioned a loop being used to generate graphs. I have some sample code partially put together but have found one offending line of code that I cannot figure out what to do with. I have one data frame called grade4. If I do something like hist(grade4$math) I get the appropriate chart. Within the loop, however, I am doing this for multiple files and grades, so I use

Hi, I'm playing with moving some of my lattice graphics into ggplot2, and I'd like to ask how to achieve a couple of things, both of which are fully illustrated in self-contained code (and mostly minimal, although that left quite a bit) following this written description. 1. I quite often like to use a 'ghosted' reference across facets - for example, in my example program below,

Hello I have a longitudinal dataframe organized in the long format and would like to make comparison between successive rows if certain conditions apply. Specifically, I have four variables of interest: grade, score, year, and schid, associated with each school with 3 measurements per school per grade, therefore the rows are temporally ordered and each school occupies multiple rows. For example,

I have data on every grade in all elementary schools in Chicago over 5 years. I would like to estimate a trend over time for each grade in each school. There are 17,600 data all together (about 460 schools, nearly 8 grades each, over 5 years). Is there a not-so-hard way to do this in R (I was thinking of using rlm)? ______________________________________________________________________ Stuart

Hello List. I have many files of ECG, each one with 7 column and I need only the second column and the name of each ECG. I am doing this but althought I have various days trying this i haven't gotten, so I ask help with this, if somebody cans help me I'll be so thankfully. --------------------------------------------------------------------------------------------------------

Hola, Esta pregunta la hice en stackoverflow <http://stackoverflow.com/questions/31137940/randomly-assign-teachers-to-classrooms-imposing-restrictions/31143808#31143808>pero nadie pudo contestarla. 1. Quiero generar N escuelas, con G grados y C divisiones. 2. Quiero asignar cada uno de T maestros a 2 divisiones en un grado y escuela Si tengo C=4 divisiones, puedo lograr lo que quiero con

I get the following error when I run qplot() qplot(grade, read,data = hhm.long.m, geom = c("point", "smooth")) Error in smooth.construct.cr.smooth.spec(object, data, knots) : x has insufficient unique values to support 10 knots: reduce k. I am not sure how to tackle this problem. When I take a subsample (< 1000) than I am able to run that function but with my sample

Dear List: I am working to generate graphs for individual students that will be created through a series of loops in Sweave. Before doing so, I am still trying to design the graph. The code for creating the barplot is below with some sample datapoints just made up for now. Ultimately, this chart will take data from an lme object using longitudinal student data. So, the dots represent the

I have a data frame that has columns Semester, Student ID (SID), Subject, Grade, Devel (Tor F). Students can have multiple records within a semester. Right now, the columns are not considered factors. I want to do an analysis that would show the number of students who received particular combinations of grades. I also need to distinguish between the two Development levels (they modify classes,

Perdon por no se lo suficientemente claro :( Tu codigo produce `validPairs` que tiene 7 variables y 360 observaciones. Donde > validPairs[1,] V1 V2 V3 V4 V5 V6 valid 60 e1 g1 c1 e1 g1 c2 Valid indica que un maestro tiene asignado c1 y c2 en la escuela e1 y el grado g1. Correcto? Si es asi, esto es casi lo que queira producir y creo que puedo llegar a donde quiero usando tu codigo de base.

has_many :through is great. Is there anyway to find the association that it went through? Example: class Student has_many :projects has_many :grades, :through => :projects end student.grades[3].project Is it clear what I''m asking? How would this be done? -- Posted via http://www.ruby-forum.com/.